eChapters

Effective crop monitoring is essential for maintaining plant health, optimizing farm operations, and improving agricultural productivity. This chapter explores the application of artificial intelligence for real-time crop monitoring and farm management. AI systems integrate information from sensors, satellites, drones, mobile devices, and other sources to assess crop conditions and identify emerging problems. Machine learning and deep learning techniques can analyse crop images, environmental parameters, growth patterns, and field conditions to provide actionable insights. The chapter examines real-time monitoring, image analysis, crop health assessment, anomaly detection, and decision-support applications. It also highlights the role of IoT and multimodal agricultural data in developing intelligent and responsive farming systems.

Introduction

Rice is the world’s most important staple crop and is a primary source of energy and nutrition for about half of the world’s population. So it is the most important cereal crop with respect to food security of common people. Due to increasing world population and shrinkage of farm land holdings there is an urgent need to increase the grain productivity. Therefore, increasing grain yield has become the primary objective in many rice-breeding programs. India is the second highest rice producer (about 120 million ton/year) in the world and able to meet the demand of rice for the entire Indian population. But along with yield improvement of rice, quality has now become a foremost consideration for rice consumers and millers. Quality is defined as “the totality of features and characteristics of a product or service that bears its ability to satisfy stated or implied needs” (International Standard Organization (ISO) 8402 1986). The concept of grain quality covers many physico-chemical properties such as grain shape and size, milling and cooking properties, amylose content, stickiness, chalkiness, texture, colour, gelatinization characters and various nutritional properties. Thus, rice grain quality generally includes five main classes i.e. (i) milling quality, (ii) physical quality, (iii) cooking and eating quality (iv) sensory quality and (v) nutritional quality. Grain quality and its assessment are very important to consumers, millers and rice breeders who are engaged in varietal improvement programme, related to new features such as high nutritional quality, high yield potential, highly resistant to abiotic or biotic stresses, higher water use efficiency etc.

Plant diseases significantly reduce crop productivity, quality, and economic returns, making early and accurate detection essential for effective crop protection. This chapter examines the application of machine learning and computer vision for identifying diseases at an early stage. It discusses agricultural image acquisition using RGB, hyperspectral, and sensor-based technologies, followed by image preprocessing, segmentation, feature extraction, and classification. Machine learning algorithms such as support vector machines, random forests, and convolutional neural networks are considered for disease recognition. The chapter also explores the integration of AI with IoT and mobile technologies and presents practical applications while addressing challenges involving datasets, environmental variability, model generalization, and computational requirements.

Abstract

Climate change is a matter of great concern considering aquatic resources and the productivity. The likely impact of Climate Change is noted in the domain both in marine as well as estuarine capture fisheries, fresh water capture fisheries and freshwater aquaculture. Climate change is having a linkage with spread of fish diseases as increasing water temperature will shift the balance in favor of either the host or pathogen changing the frequency and distribution of diseases. There are a no of adaptation and mitigation measures in aquaculture in order to increase the productivity and properly maintain the survivability of many aquaculture species.

Elevation or height data of land surface above a defined vertical datum is stored in the form of raster grids which is known as Digital Elevation Model (DEM). The DEM data can be processed to derive many useful parameters like slope, aspect, curvature, roughness, etc. This process of quantitatively describing terrain obtained from DEM data through computation of many variables is known as Digital Terrain Analysis. Digital terrain analysis has applications in the various fields like hydrology, ecology, geomorphology, etc. DEM data for digital terrain analysis are available from the satellites like ASTER (Advanced Spaceborne Thermal Emission and Reflection Radiometer), Cartosat, ALOS (Advanced Land Observation Satellite), and SRTM (Shuttle Radar Topography Mission).

In this exercise, we are going to discuss the derivation of some primary and secondary terrain attributes from DEM data in R software. For performing digital terrain analysis in R, following packages are required.

Introduction

Vast proportions of the population of the world are dependent on plants as their principal source of food either directly or indirectly. Recent decades have also seen increased numbers of people turning to alternative medical therapy based upon traditional folk medicine or food as a form of medicine. These alternative therapies emphasise the importance of a ‘good diet’ in maintaining and restoring health. Under these circumstances, vast majority of population may see diet therapy, dietary supplements and non-invasive alternative therapies as a safer, less technological and more natural way of maintaining health and treating and preventing individuals from illness. These alternatives may be seen as empowering the consumer and shifting the locus of control away from the medical establishment. This chapter covers many crucial topics to understand the chemistry and bioactivity of the active compounds of plant origin. It also aims to cover the latest research on the bioactive compounds.

5.1    Population Growth
    
5.2    Exponential Growth
    
5.3    Population Explosions
    
5.4    Over Population
    
5.5     The Causes of Rapid Population Growth
    
5.6    Ways and Means to Solve Over Population
    
5.7    Environment and Health
    
5.8    Family Welfare Programme
    
5.9    Human Rights
    
5.10    Child Welfare
    
5.11    Women Welfare

11.1 INTRODUCTION

Plant growth regulators have remained an important component in horticulture from time immemorial because they were effective means of quantitative as well as qualitative improvement in growth and development of crops. Plant Growth Regulators (PGR) are diverse group of organic compounds other than nutrients, produced artificially or by plants which in low concentrations promote, inhibit or modify the physiological process in plant. The term includes both naturally occurring phytohormones as well as synthetic compounds. These are produced naturally in higher plants, controlling growth or other physiological functions at a site remote from its place of production and active in minute amounts. Plant Growth Regulators are used in different forms like liquid, powder, paste etc. “Hormone” is Greek word derived from “hormao”, which means to stimulate. Thimone (1948) suggested the use of term ‘phytohormones’ as the organic substance, which are produced naturally in plants, synthesised in one Part And usually translocated to other part wherein every small quantity affects the growth and other physiological function of the plants. To distinguish them from the animal hormones they are termed as phytohormones. Auxin was the first hormone to be discovered in plants and at one time considered to be only naturally occurring plant growth hormone. The role of plant growth regulators in various physiological processes such as seed germination, f lowering, fruiting, seed development, fruit ripening and yield etc. in different crop plants is well established (Kiran et al., 2011). There are five classical phytohormones: auxins, gibberellins, cytokinins, ethylene and abscisic acid. Besides classical phytohormones a variety of other compounds that play roles in plant growth and development have also been identified, including jasmonic acid, salicylic acid, brassinosteroids and polyamines (Basra, 2000). The application of plant growth regulators in agriculture has started in 1930 in the United States. Ethylene, a naturally occurring substance, is one of the first plant growth regulators being discovered and used successfully for enhancing f lower production in pineapple (Fishel, 2006). Its toxic effects to human beings are low.

Introduction

Expanding human and livestock population, fast-growing industrial requirements and urbanization are putting ever-increasing pressures on land resources, creating competition and conflicts which results in sub-optimal use of both land and its natural resources. With no additional land for horizontal expansion of agriculture, there is an urgent need to find viable technologies for enhancing productivity and resource conservation on a sustainable basis. In this context, Agroforestry offers huge potential not only to diversify and increase overall land productivity to meet the demands of fuel, fodder, timber, medicine and other non-woody forest products but also to enhance green cover, and reduce the pressure on forest (Chavan et al. 2016; Handa et al., 2016). Agroforestry offers an affordable alternative in place of expensive conventional conservation measures for providing insurance against risks caused due to weather aberrations, controlling erosion hazards and ensuring sustainable production of the land on a long-term basis. The main objective of agroforestry is to take the advantage of complementary relationships between trees, crops, and livestock in such a way so that sustainability, productivity stability, and profitability of the system is maintained. In India, agroforestry practices are important component in the various developmental programmes schemes like Flood Control/Management Programmes, Multipurpose River Valley Projects, Agriculture Development Programmes, Integrated Rural Development Programmes (IRDP), National Watershed Development Programme for Rainfed Areas (NWDPRA), Forestry Development Scheme, Drought Prone Area Development Programme (DPAP) and Desert Development Programme (DDP) from government sector and wood based industry from private sector. After 2000 a transitional shift in agroforestry observed to tackle the ill effects of intensive agriculture, climate change and nutritional security. Under changing climatic scenarios agroforestry rose as a silver bullet to offer not only single benefits but also a basket of multiple benefits. In the present chapter a journey of agroforestry research and developments, region-specific models, area under agroforestry, initiative of government on policy aspects and challenges are elaborated extensively.

9.1 Introduction

Biomass conversion is a transformative process that harnesses the energy and chemical potential of organic materials derived from living organisms. It encompasses various methods of converting biomass, including agricultural residues, forestry by-products, algae, and even waste materials, into valuable products such as biofuels, chemicals, and energy. This process is a cornerstone of sustainable resource utilization and plays a critical role in addressing environmental concerns, reducing reliance on fossil fuels, and promoting a circular economy. Biomass conversion methods range from biochemical processes like fermentation and anaerobic digestion to thermochemical processes such as combustion, pyrolysis, gasification, and liquefaction. Each method employs distinct conditions, catalysts, and technologies to break down complex biomass structures and convert them into desired products.

Agriculture has progressed from labour-intensive traditional practices through mechanization and the Green Revolution to precision agriculture and Agriculture 5.0. This chapter traces that historical development and identifies limitations associated with conventional farming, including inefficient resource use, environmental degradation and weak adaptability. It explains how GPS-guided machinery, sensors and precision technologies prepared the foundation for intelligent systems. Artificial neural networks, deep learning and fuzzy logic now process data from IoT devices, UAVs and satellites to support automated irrigation, crop monitoring and soil analysis. The chapter emphasizes that integrating human knowledge with computational power is increasingly essential for global food security, sustainability and climate resilience.

Increasing crop productivity while reducing resource consumption is a central objective of modern agriculture. This chapter examines how artificial intelligence can support crop yield improvement through data-driven analysis, prediction, and decision-making. AI models can integrate information from soil, weather, crop growth, remote sensing, IoT sensors, and historical yield records to identify important factors influencing productivity. Machine learning and deep learning approaches can support yield forecasting, crop selection, fertilizer and water optimization, and precision management. The chapter also considers AI-enabled genomic selection, market intelligence, and intelligent farm management. Challenges such as data availability, implementation cost, connectivity, farmer training, and model reliability are discussed alongside future opportunities including edge AI and explainable AI.

Fruit Flies and Economic Importance

Fruit flies belong to order Diptera (true flies) with one of the largest, most diversified and fascinating acalypterate family Tephritidae. These are commonly called as fruit flies due to their close association with fruits and vegetables and are also known as peacock flies because of their habit of strutting about and vibrating spotted and striped wings. Of the 4500 known species of fruit flies worldwide, nearly 200 are considered as pests but 70 species are regarded as agriculturally important throughout the world (Clarke et al., 2005, Schutz et al., 2012). David and Ramani (2011) reported 325 species in the Indian subcontinent of which 243 in 79 genera are from India alone. Important fruits flies damaging fruit crops in India include Oriental fruit fly or mango fruit fly, Bactrocera dorsalis (Hendel); peach fruit fly, B. zonata (Saunders); guava fruit fly, 
B. correcta (Bezzi); melon fly, B. cucurbitae (Coquillett) and ber fruit fly, Carpomyia vesuviana Costa, whereas important fruit flies in Punjab include B. dorsalis and B. zonata. Important host plants of B. dorsalis are mango, guava, peach, citrus, pear, ber and loquat but most preferred host of B. dorsalis is guava while that of B. zonata are guava, peach, mango, pear, ber, citrus and loquat but C. vesuviana infests only ber (Mann 1990, Sharma et al., 2005, Singh 2008b, Singh 2012, Singh et al., 2014a,b and Singh et al., 2015). Bactrocera dorsalis is considered to be the most damaging and aggressive fruit flies in the world (Leblance and Putao 2000). They are strong fliers and can fly upto two kilometers in search of food (Butani 1979).

Introduction

Pulses are major and cheap sources of protein in Indian vegetarian diet, providing most of the essential amino acids. Pulses are mainly consumed in the form of dehusked split pulses (Dal); and have 15-24% proteins. Various types of pulses grown are pigeon pea, chickpea, black gram, green gram, lentil, etc. Pulses are consumed because of body building properties due to the presence of various amino acids. By-products of pulses like leaves, pod coats and bran are fed to animals in the form of dry fodder. Some pulse crops like gram, lobia, urd bean & moong bean are fed to animals as green fodder.

1.    The predominant form of fat within fat (adipose) tissue is stored in humans in the form of

(a) Glycogen

(b) Triglycerides

(c) Diglycerides

(d) Monoglycerides

2.    The Thermic Effect of food refers to

(a) The ‘heat’ one feels from eating a chili pepper

(b) The amounts of energy the body spents to process, use and store

(c) The benefits of eating warm foods in cold weather

(d) All of the above

Historically, humans have utilized animal skins for various purposes including shelter, clothing, weapons, and food containers. In contemporary times, skins and hides significantly contribute to foreign exchange earnings within the animal husbandry sector and are widely employed by the leather industry. At slaughterhouses, hides and skins are generally collected and dispatched to tanneries on the same day. If a tannery is not in close proximity, hides are preserved through salting or curing prior to being transported in batches.
A skin (the outer covering) from a fully grown large animal is termed a hide; it is comparatively large, thick, and heavy, typically exceeding 30 lb (13.62 kg) for cattle or buffalo. Conversely, the outer covering of smaller animals such as sheep, goats, pigs, and young calves is known as skin. This type is smaller, thinner, and lighter. The term “slunk” refers to the skin of an unborn calf, which is often utilized for parchment, light suede, or drum skins. Calf skin is derived from young calves that have not yet reached maturity, and it is generally softer and more delicate than the hides of older animals. Its fine texture renders it highly sought after for premium leather goods. In contrast, kip skin is obtained from older but still immature calves. It is thicker and more robust than calf skin while being more refined than adult hides. Kip skin is recognized for its blend of durability and softness, making it ideal for longlasting leather products.
Hides and skins constitute approximately 4-11% of an animal’s live weight, influenced by factors such as species, age, breed, and health. In cattle, the average hide yield is about 7% of live weight, whereas in sheep and goats, the average skin yield is around 11% of live weight. Hides and skins rank among the most valuable by-products of animals and are transformed into leather through the tanning process. The trimmings are repurposed for the production of glue, artifacts, or as feed supplements.

For nations where agriculture is intrinsically linked to the rhythms of the monsoon, the need for effective climate guidance and resilient farming practices is particularly acute. The preceding chapters have likely underscored the profound impact of climate variability, especially the unpredictable nature of monsoon patterns, on agricultural productivity and the livelihoods of millions. This chapter turns its attention to the essential infrastructure development and enabling policy frameworks required to empower farmers in monsoon-dependent countries to navigate the uncertainties of their climate and build lasting prosperity. Given the unique challenges and opportunities presented by monsoon climates, this chapter will specifically explore the development of infrastructure that supports climate-resilient agriculture in these regions. This includes a focused examination of:
• Specialized Weather Observation and Forecasting Infrastructure for Monsoon Monitoring: Emphasizing the need for advanced systems dedicated to accurately monitoring monsoon onset, intensity, spatial distribution, and predicting extreme events like heavy rainfall and prolonged dry spells, which are critical for timely agricultural decisions.
• Communication and Dissemination Infrastructure Tailored for Monsoon-Related Risks: Focusing on effective and accessible channels to deliver critical monsoon forecasts, advisories on managing water excesses and deficits, and information on appropriate cropping strategies during and between monsoon seasons, reaching even remote agricultural communities.
• Infrastructure for Enhanced Water Management in a Monsoon Context: Addressing the dual challenges of managing excess water during intense monsoon periods (including flood mitigation and drainage systems) and ensuring water availability during dry spells through efficient irrigation, water harvesting, and groundwater management infrastructure.
• Data Management and Analysis Focused on Monsoon-Driven Agricultural Systems: Highlighting the importance of analyzing historical and real-time data related to monsoon patterns and their impact on specific crops and regions to generate localized and timely agricultural guidance.
The chapter will also critically analyze the enabling policies necessary to support climate-resilient agriculture within the specific context of monsoondependent nations. This will involve exploring:

Introduction

The competition between human and livestock population for the existing animal and plant resources has been of great concern to the poultry nutritionists. Today the poultry industry has already challenged by the high price of the feed ingredients. Moreover in the next century there will be a shortage of conventional feed stuffs for use in poultry production. Efforts are on to look forward for the new feed resources and to evaluate them for their inclusion in the poultry ration. However many of the feed stuffs are characterized by the presence of certain incriminating factors. The incorporation of feed stuffs containing incriminating factors may adversely affect the performance of poultry. The nutritional strategy involving the use of feed enzymes offer immense potential to overcome the problems. The use of enzymes in feed mixtures of growing poultry particularly for young chicks has been the subject of much research activity in the recent decades. The interest in the feed enzymes is a reflection in changing the attitude of the society and the economic climate of the feed industry. It has been seen that approximately 187 million metric tons of cereal grains (FAO, 2011) and 26.02 million tons oil seeds as per the trade estimate for 2011-12 are produced in India which yield non starch polysaccharides (NSP) as a part of variety of products.

INTRODUCTION

Rabbit production is the upcoming livestock farming throughout the world. The domestic rabbit are raised meat, fur –skins and wool. Climatic condition of Karnataka are not favourable for raising wool breeds of rabbits, but are definitely well for broiler rabbit production.

Rabbits require less space for housing and highly prolific. Initial investment for rabbits farming is very less and maintenance cost is also very low. There is no religious barriers in rabbit meet consumption and rabbit meat contains very low cholesterol when compared to the other meats.

Rabbit farming can be very well fit into mixed farming systems. It can be adopted by small and marginal for maximum utilization of lands and resources, and to derive substantial income under rural condition.